Ray Tracing Structured AMR Data Using ExaBricks

TL;DR

This paper introduces a GPU-accelerated ray tracing method for Structured AMR data that enables interactive, high-quality visualization with efficient data access and minimal memory overhead.

Contribution

It presents a novel combination of data structures and GPU techniques for efficient volume and iso-surface rendering of Structured AMR data.

Findings

Achieves high-performance rendering on GPU workstations.

Supports interactive transfer function and iso-surface adjustments.

Maintains low memory overhead during visualization.

Abstract

Structured Adaptive Mesh Refinement (Structured AMR) enables simulations to adapt the domain resolution to save computation and storage, and has become one of the dominant data representations used by scientific simulations; however, efficiently rendering such data remains a challenge. We present an efficient approach for volume- and iso-surface ray tracing of Structured AMR data on GPU-equipped workstations, using a combination of two different data structures. Together, these data structures allow a ray tracing based renderer to quickly determine which segments along the ray need to be integrated and at what frequency, while also providing quick access to all data values required for a smooth sample reconstruction kernel. Our method makes use of the RTX ray tracing hardware for surface rendering, ray marching, space skipping, and adaptive sampling; and allows for interactive changes to the transfer function and implicit iso-surfacing thresholds. We demonstrate that our method achieves high performance with little memory overhead, enabling interactive high quality rendering of complex AMR data sets on individual GPU workstations.